Improper input validation in Google Tensorflow
CVE-2022-41901
TensorFlow is an open source platform for machine learning. An input `sparse_matrix` that is not a matrix with a shape with rank 0 will trigger a `CHECK` fail in `tf.raw_ops.SparseMatrixNNZ`. We have patched the issue in GitHub commit f856d02e5322821aad155dad9b3acab1e9f5d693. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Vulnerability class: Drupalgeddon 2 (CVE-2018-7600)
EPSS: 0.004 (36.1th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 4.8 (Medium). Vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H.
Affected products
- Google Tensorflow
- Tensorflow — versions >= 2.10.0, < 2.10.1, >= 2.9.0, < 2.9.3, < 2.8.4
Weakness classification (CWE)
Public proof-of-concept exploits
References
- security-advisories@github.com (Exploit, Patch, Third Party Advisory)
- security-advisories@github.com (Patch, Third Party Advisory)
- security-advisories@github.com (Third Party Advisory)
Frequently asked questions
- What is CVE-2022-41901?
- CVE-2022-41901 is a medium-severity vulnerability in Google Tensorflow, classified under Improper Input Validation. CVSS score: 4.8/10. Published 2022-11-18.
- How severe is CVE-2022-41901?
- Medium severity. CVSS v3 base score is 4.8 out of 10.
- Is CVE-2022-41901 known to be exploited?
- 2 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.